Understanding End‐of‐Century Snowpack Changes Over California's Sierra Nevada. Issue 2 (29th January 2019)

• Record Type: Journal Article
• Authors: Sun, Fengpeng; Berg, Neil; Hall, Alex; Schwartz, Marla; Walton, Daniel
• Is Part Of: Geophysical research letters. Volume 46:Issue 2(2019)
• Page Start: 933
• Page End: 943
• Publication Date: 2019-01-29
• Subjects: regional climate -- climate downscaling -- Sierra Nevada -- snowpack -- projections -- climate change; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2018GL080362
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: This study uses dynamical and statistical methods to understand end‐of‐century mean changes to Sierra Nevada snowpack. Dynamical results reveal that middle‐elevation watersheds experience considerably more rain than snow during winter, leading to substantial snowpack declines by spring. Despite some high‐elevation watersheds receiving slightly more snow in January and February, the warming signal still dominates across the wet season and leads to notable declines by springtime. A statistical model is created to mimic dynamical results for 1 April snowpack, allowing for an efficient downscaling of all available general circulation models from the Coupled Model Intercomparison Project phase 5. For all general circulation models and emission scenarios, dramatic 1 April snowpack loss occurs at elevations below 2, 500 m, despite increased precipitation in many general circulation models. Only 36% (±12%) of historical 1 April total snow water equivalent volume remains at the century's end under a "business‐as‐usual" emission scenario, with 70% (±12%) remaining under a realistic "mitigation" scenario. Plain Language Summary: The Sierra Nevada is one of California's most beloved natural treasures, and mountain snowpack snow is an important water resource. As climate change continues, scientists and water managers have become increasingly concerned about the future of the frozen reservoir Californian depend on. Global climate models are the best tools we have for projecting future climate change. But they are too coarse in spatial resolution to accurately simulate future climate in topographically complex areas like the Sierra Nevada, where different elevations experience different climatic conditions. This study utilizes an innovative hybrid high‐resolution downscaling method to understand spatial and temporal patterns of snowpack changes for certain watersheds and different elevations in the Sierra Nevada. A full range of global climate models and future greenhouse emission scenarios are investigated to quantify the uncertainties. Dramatic decreases in total Sierra Nevada snowpack are projected by century's end, even under a realistic mitigation emission scenario. The results are intended to provide water resource and management agencies information to help plan for the impacts of future climate change on the reliability and inhomogeneity of water supplies. Key Points: Dynamically downscaled projections are used to understand spatial and temporal patterns of snowpack changes for Sierra Nevada watersheds A hybrid dynamical‐statistical downscaling technique is developed to project 1 April snowpack change by century's end for all GCMs and RCPs Dramatic decreases in total snowpack volume are projected by century's end, even under a realistic mitigation emission scenario